---
title: "ml-workgroup/covid-19-image-repository: papers citing it"
description: "4 papers in the tracked journals link to the GitHub repository ml-workgroup/covid-19-image-repository in their Crossref records, the first in 2022; most of them (2) in 2023."
url: https://scholar4ai.com/code/github-ml-workgroup-covid-19-image-repository
markdown_url: https://scholar4ai.com/code/github-ml-workgroup-covid-19-image-repository.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "4 papers in the tracked journals link to the GitHub repository ml-workgroup/covid-19-image-repository in their Crossref records, the first in 2022; most of them (2) in 2023. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# ml-workgroup/covid-19-image-repository: papers linking to it

Research papers in the 480 tracked journals that link to ml-workgroup/covid-19-image-repository (https://github.com/ml-workgroup/covid-19-image-repository), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 45 stars
- 19 forks
- Python
- created 2020
- https://github.com/ml-workgroup/covid-19-image-repository

All repositories: https://scholar4ai.com/code.md

## Key findings

- 4 papers in the tracked journals link to the GitHub repository ml-workgroup/covid-19-image-repository in their Crossref records, the first in 2022; most of them (2) in 2023.
- By category: AI (4); the journals with the most are Nature Machine Intelligence (1), Expert Systems with Applications (1) and Neural Computing and Applications (1).

## By year

*Papers linking to ml-workgroup/covid-19-image-repository by publication year*

| Year | Papers |
|---|---:|
| 2022 | 1 |
| 2023 | 2 |
| 2025 | 1 |

## Journals

*Journals whose papers link to ml-workgroup/covid-19-image-repository most*

| Journal | Papers |
|---|---:|
| [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 1 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 1 |

## Papers

*Papers linking to ml-workgroup/covid-19-image-repository, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2023-05-27 | [Parallel CNN-ELM: A multiclass classification of chest X-ray images to identify seventeen lung diseases including COVID-19](https://doi.org/10.1016/j.eswa.2023.120528) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Md. Nahiduzzaman, Md. Omaer Faruq Goni, Rakibul Hassan et al. | 74 | cites it |
| 2022-07-07 | [WatMIF: Multimodal Medical Image Fusion-Based Watermarking for Telehealth Applications](https://doi.org/10.1007/s12559-022-10040-4) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Kedar Nath Singh, Om Prakash Singh, Amit Kumar Singh et al. | 48 | cites it |
| 2025-03-17 | [Explainable AI reveals Clever Hans effects in unsupervised learning models](https://doi.org/10.1038/s42256-025-01000-2) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Jacob Kauffmann, Jonas Dippel, Lukas Ruff et al. | 35 | cites it |
| 2023-11-20 | [An integrated convolutional neural network with attention guidance for improved performance of medical image classification](https://doi.org/10.1007/s00521-023-09164-x) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Coşku Öksüz, Oğuzhan Urhan, M. Kemal Güllü | 23 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). ml-workgroup/covid-19-image-repository: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-ml-workgroup-covid-19-image-repository

```bibtex
@misc{scholar4ai-code-github-ml-workgroup-covid-19-image-repository,
  author = {{Scholar4AI}},
  title = {ml-workgroup/covid-19-image-repository: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-ml-workgroup-covid-19-image-repository}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).